Evidence map›Paper›PMID 42634679›Full record

ArticleJournal of inflammation research2026

Integrative Multi-Omics Mendelian Randomization Identifies BLMH as a Keratinocyte-Enriched Protective Candidate Gene and Potential Therapeutic Target in Psoriasis.

Rui Shen, Binyi Ran, Jiazheng Liu, Xiaolong Li, Hui Cao, Qingbo Liu, Bin Liang, Meilan Xie, Junfeng Hou, Jintao Gao

Abstract read
In one paragraph

Article in Journal of inflammation research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Rui Shen *School of Artificial Intelligent Medicine, Guilin Medical University, Guilin, Guangxi, People's Republic of China.
Binyi Ran *School of Artificial Intelligent Medicine, Guilin Medical University, Guilin, Guangxi, People's Republic of China.ORCID 0009-0007-8281-4399
Jiazheng Liu *College of Basic Medicine, Guilin Medical University, Guilin, Guangxi, People's Republic of China.
Xiaolong LiSchool of Artificial Intelligent Medicine, Guilin Medical University, Guilin, Guangxi, People's Republic of China.
Hui CaoKey Laboratory of Medical Biotechnology and Translational Medicine, Education Department of Guangxi Zhuang Autonomous Region, Guilin Medical University, Guilin, Guangxi, People's Republic of China.
Qingbo LiuCollege of Basic Medicine, Guilin Medical University, Guilin, Guangxi, People's Republic of China.
Bin LiangCollege of Basic Medicine, Guilin Medical University, Guilin, Guangxi, People's Republic of China.
Meilan XieKey Laboratory of Cell and Gene Therapy for Regional High-Incidence Diseases, Education Department of Guangxi Zhuang Autonomous Region, Guilin Medical University, Guilin, Guangxi, People's Republic of China.
Junfeng HouSchool of Artificial Intelligent Medicine, Guilin Medical University, Guilin, Guangxi, People's Republic of China.
Jintao GaoKey Laboratory of Cell and Gene Therapy for Regional High-Incidence Diseases, Education Department of Guangxi Zhuang Autonomous Region, Guilin Medical University, Guilin, Guangxi, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Psoriasis is a chronic immune-mediated inflammatory skin disease driven by complex interactions between genetic susceptibility, immune dysregulation, and keratinocyte dysfunction. Although genome-wide association studies have identified numerous risk loci, most studies have focused on genetic associations rather than causal inference, limiting the identification of effective therapeutic targets. We employed an integrative multi-omics strategy to identify causal genes and potential therapeutic candidates for psoriasis. Methods: We integrated psoriasis genome-wide association study (GWAS), expression quantitative trait loci (eQTL), and protein quantitative trait loci (pQTL) datasets to perform two-sample Mendelian Randomization (MR) analyses and prioritize high-confidence causal genes. Most genetic datasets were derived from European-ancestry populations. Single-cell transcriptomic analysis was then used to determine their cell-type-specific expression patterns. Finally, drug-target prediction and molecular docking were applied to identify potential therapeutic compounds. Results: Integrative MR analyses indicated that genetically predicted higher BLMH expression and plasma protein levels were significantly associated with reduced psoriasis risk, with colocalization analysis supporting shared causal variants at the BLMH locus. Single-cell transcriptomics further demonstrated keratinocyte-enriched expression of BLMH and marked downregulation in psoriatic lesional skin. Drug screening using DSigDB combined with molecular docking identified tamibarotene as a potential BLMH-binding compound with favorable docking affinity. In vitro experiments showed that tamibarotene treatment was associated with increased BLMH expression and reduced KRT16, IL6, and IL8 expression in the M5-stimulated HaCaT model. Conclusion: Our integrative multi-omics analysis nominates BLMH as a keratinocyte-enriched protective candidate gene in psoriasis and suggests tamibarotene as a potential repurposed compound for further investigation. However, the experimental validation remains preliminary, and further mechanistic, in vivo, and translational studies are required to validate these findings.

Indexed as

BLMHeQTLmendelian randomizationpQTLpsoriasis

Identifiers

PMID42634679
PMCPMC13499991

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.